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Tytuł artykułu

A probabilistic method for ordering group of intervals

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A probabilistic approach to the ordering of intervals is developed. The method is based on the assumption that random variables are independently and uniformly distributed at given intervals. It allows all possible cases of interval location and intersection and of ordering of interval and real number to be taken into account. Additionally, this method al-lows the widths of the intervals to be taken into account in the ordering procedure. It should be noted that the probabilistic approach was used only to infer the set of formulae needed to estimate quantitatively the degree to which one interval is less or equal to another interval. The measure of such a degree may be treated formally as one of probability, but the term "possibility" tan be also used, as it better reflects the sense of the relation between the intervals in many cases.
Rocznik
Strony
45--53
Opis fizyczny
Bibliogr. 14 poz., 2 rys., 1 tab.
Twórcy
  • Institute of Mathematics and Computer Science, Technical University of Częstochowa Dąbrowskiego 73, 42.200 Częstochowa
autor
  • Institute of Mathematics and Computer Science, Technical University of Częstochowa Dąbrowskiego 73, 42.200 Częstochowa
  • Institute of Mathematics and Computer Science, Technical University of Częstochowa Dąbrowskiego 73, 42.200 Częstochowa
Bibliografia
  • [1] Fit R.J., Propagating temporal constrains for scheduling, Proc. Fifth National Conf. on AI (AAAI 86), Morgan Kaufmann, Loa Atos 1986, 383-388.
  • [2] BerttinyC., A formalization of interval based temporal subsumption in first order logic, Foundation, of Knowledge Representation and Reasonin Lect. Notes In AI 810, Springer Verlag, Berlin 1994,53-73.
  • [3] Kulpa Z., Diagrammatic representation for a space of intervals, Machine Graphics and Vision 1997, 6, 1, 5-24.
  • [4] Diamond Ph., Kloeden P., Metric spaces of fuzzy sets, Fuzzy Setsand Systems 1990, 35, 241-251.
  • [5] Helpern S., Using distance between fuzzy numbers in socio-economic systems, (w:) R. Trapl (ed.) Cybernetic and Systems, World Scientific, Singapor 1994, 279-286.
  • [6] Helpern S., Representation and application of fuzzy numbers, Fuzzy Sets and Systems 1997, 91, 259-268.
  • [7] Moore R.E., Interval Analysis, Prentice-Hall Englewood Cliffs, New York 1966.
  • [8] Ishihichi H., Tanaka M., Multiobjective programming in optimization of the interval objective function, European Journal of Operational Research 1990, 48, 219-225.
  • [9] Chanas S., Kuchta D., Multiobjective programming in optimization of the interval objective functions-a generalized approach, European Journal of Operational Research 1996, 94, 594-598.
  • [10] Walster G.W., Bierman M.S., Innterval Arithmetic in Forte Developer Fortran, Technical Report. Sun Microsystems (March 2000).
  • [11] C++ Interval Arithmetic Library Reference. http://docs.sun.com/htmlcollcoll.693/iso-8859-1/CPPARIT.../iapg ref man.htm.
  • [12] Sevastianov P., VenbergA., Modeling and optimization of work of the power units under interval uncertainty, Energetics 1998, 3, 66-70 (in Russian).
  • [13] Sevastianov P., Valkovsky V., The procedure of fuzzy interval simulation of technology--economic systems, Information Technologies 1999, 6, 23-26 (in Russian).
  • [14] Sevastianov P., Valkovsky V., The simulation of technological processes in logistics under condition of fuzzy initial data, Resources, information, supply, Competition 1999, 2-3, 79-83 (in Russian).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPG5-0015-0063
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